Date Approved
8-11-2022
Graduate Degree Type
Project
Degree Name
Computer Information Systems (M.S.)
Degree Program
School of Computing and Information Systems
First Advisor
Robert Adams
Academic Year
2022/2023
Abstract
Coronavirus or COVID-19 is considered the most infectious and deadly disease developed by the virus called SARS-CoV-2 and they have reported different variants like 2019-nCoV and MERS- CoV. According to the World health organization (WHO), more than 583,235,205 cases have been registered among them 6,420,220 has been dead this is the reason they have called it a global health crisis and they mainly spread through the infected droplets. The only way to prevent this virus from spreading from an infected person is by wearing a mask. The virus can be easily spread when people gather in huge numbers and in confined small areas with poor ventilation systems and monitoring them manually to check whether the individual is wearing a mask is not possible to resolve this issue face detection method has been proposed which uses OpenCV to check whether the people are wearing the mask or not wearing the mask. For performing this analysis a webcam is needed to track the human faces. This project uses an image dataset that has human faces with and without masks the model is trained on the image dataset and the prediction is done in real-time.
ScholarWorks Citation
Kondala, Rithwik Sagar, "Face Mask Detection Model" (2022). Culminating Experience Projects. 236.
https://scholarworks.gvsu.edu/gradprojects/236
